For sure. I can speak to my own experience.
I’m on the Data Science team at Codecademy. Prior to joining Codecademy I did most of my statistical analysis and data cleaning in R. When I started here I quickly realized I needed to brush up on SQL and Python to work effectively across different teams and departments.
I ramped up on SQL pretty quickly because I was using it every day to grab and manipulate data for ETLs and ad-hoc queries/analyses. SQL is such an essential language in any collaborative working environment because it often the language everyone knows (or can at least read and understand what’s going on).
With Python, I needed a slightly more guided, hands-on approach. So I worked through our Learn Python 3 course. While I still use R for most of my programming and analysis needs, it is incredibly helpful to be able to read Python. For example, our Data Engineering team writes some scripts in Python and knowing it has been helpful when working them like reviewing Pull Requests, etc.
I think our Data Scientist Career Path does a good job of covering this suite of languages (SQL, Python, R) and showing how they can be used together throughout the data science workflow (i.e. getting and manipulating data, analyzing data, communicating results, etc). For me, the key thing about working in industry is that it is highly collaborative. And being able to work in different modes and languages really helps with that.
As an aside, I am also excited by some of our newer content like Apply Natural Language Processing with Python, which I will definitely check out even if I am not actively working on NLP problems. I just know it’s going to be cool.